Feature extraction within images holds a multitude of uses over multiple industries. The identification of elements or features within an image, or even absent from an image, provides valuable information. Prior art uses of human identification, however, wastes time and energy, in addition to variances between human extractors.
For example, residential and/or commercial property owners approaching a major roofing project may be unsure of the amount of material needed and/or the next step in completing the project. Generally, such owners contact one or more contractors for a site visit. Each contractor must physically be present at the site of the structure in order to make a determination on material needs and/or time. The time and energy for providing such an estimate becomes laborious and may be affected by contractor timing, weather, contractor education, and the like. Estimates may be varied even between contractors in determination of estimated square footage causing variance in supply ordering as well. Additionally, measuring an actual roof may be costly and potentially hazardous—especially with steeply pitched roofs. Completion of a proposed roofing project may depend on ease in obtaining a simplified roofing estimate and/or obtaining reputable contractors for the roofing project.
Remote sensing technology has the ability to be more cost effective than manual inspection while providing pertinent information for assessment of roofing projects. Images are currently being used to measure objects and structures within the images, as well as to be able to determine geographic locations of points within the image when preparing estimates for a variety of construction projects, such as roadwork, concrete work, and roofing. See for example U.S. Pat. No. 7,424,133 that describes techniques for measuring within oblique images. Also see for example U.S. Pat. No. 8,145,578 that describe techniques for allowing the remote measurements of the size, geometry, pitch and orientation of the roof sections of the building and then uses the information to provide an estimate to repair or replace the roof, or to install equipment thereon. Estimating construction projects using software increases the speed at which an estimate is prepared, and reduces labor and fuel costs associated with on-site visits.
Further, feature extraction, or cataloguing feature extraction, can go beyond features represented within an image and provide useful information on features missing from an image. For example, tree density within a forest, or changes to the tree density over time, may be determined using lack of trees, a feature within a known area of an image. Thus, the location of missing feature may be determined relevant in feature extraction of the image.